A novel variable selection method based on frequent pattern tree for real-time traffic accident risk prediction

出版年份 2015 全文链接

标题

A novel variable selection method based on frequent pattern tree for real-time traffic accident risk prediction

作者

关键词

Frequent Pattern tree (FP tree), Fuzzy C-means clustering (FCM), Bayesian network, k Nearest Neighbor (, k, -NN), Variable importance, Variable selection, Random forest, Real time, Relative Object Purity Ratio (ROPR), Traffic accident risk prediction

出版物

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Volume 55, Issue -, Pages 444-459

出版商

Elsevier BV

发表日期

2015-05-09

DOI

10.1016/j.trc.2015.03.015

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